PROGRAMS #Python Program to create the dataframe with following values
ADVANCE OPERATIONS ON DATAFRAMES
PROGRAMS
#Python Program to create the dataframe with following values
Name of Employee 0 Mohak 1 Vijay 2 Tapasi 3 Mansi
Sales Quarter State
1000 300 400 500
1 Rajasthan 1 Panjab 1 Gujarat 1 Goa
4 Bipin 5 Mohak 6 Vijay 7 Tapasi 8 Mansi 9 Bipin 10 Mohak 11 Vijay 12 Tapasi 13 Mansi 14 Bipin 15 Mohak 16 Vijay 17 Tapasi 18 Mansi 19 Bipin
800 1000
500 700
50 60 1000 900 750 200 300 1000 900 250 750 50
1 Rajasthan 2 Gujarat 2 Panjab 2 Gujarat 2 Rajasthan 2 Rajasthan 3 Rajasthan 3 Panjab 3 Gujarat 3 Goa 3 Gujarat 4 Panjab 4 Panjab 4 Gujarat 4 Goa 4 Rajasthan
from pandas import DataFrame Employees = {'Name of Employee': ['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi', 'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales': [1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4], 'State': ['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan'] } df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State']) print (df)
#Find total sales per employee in above dataframe
from pandas import DataFrame Employees = {'Name of Employee': ['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi', 'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales': [1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4], 'State': ['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan'] } df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State']) print (df) pivot = df.pivot_table(index=['Name of Employee'], values=['Sales'], aggfunc='sum') print (pivot)
OUTPUT
Name of Employee Bipin Mansi Mohak Tapasi Vijay
Sales
1210 1500 4000 2100 2600
#Find total sales by state in above dataframe
from pandas import DataFrame Employees = {'Name of Employee': ['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi', 'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales': [1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4], 'State': ['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan'] } df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State']) print (df) pivot = df.pivot_table(index=['State'], values=['Sales'], aggfunc='sum') print (pivot)
OUTPUT
State Goa Gujarat Panjab Rajasthan
Sales
1450 3400 3600 2960
#Find total sales by both employee& state in above dataframe
from pandas import DataFrame
Employees = {'Name of Employee':
['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi',
'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales':
[1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4],
'State':
['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth
an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan']
}
df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State'])
print (df)
pivot = df.pivot_table(index=['Name of Employee','State'], values=['Sales'], aggfunc='sum')
print (pivot)
OUTPUT
Sales
Name of Employee
State
Bipin
Gujarat
300
Rajasthan
910
Mansi
Goa
1450
Rajasthan
50
Mohak
Gujarat
1000
Panjab
1000
Rajasthan
2000
Tapasi
Gujarat
2100
Vijay
Panjab
2600
#Find Max individual sale by State in above dataframe
from pandas import DataFrame
Employees = {'Name of Employee':
['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi',
'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales':
[1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4],
'State':
['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth
an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan']
}
df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State'])
print (df)
pivot = df.pivot_table(index=['State'], values=['Sales'], aggfunc='max')
print (pivot)
OUTPUT
Sales
State
Goa
750
Gujarat
1000
Panjab
1000
Rajasthan
1000
#Find Mean, median and min sales by State in above
dataframe
from pandas import DataFrame Employees = {'Name of Employee': ['Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin','Mohak','Vijay','Tapasi','Mansi', 'Bipin','Mohak','Vijay','Tapasi','Mansi','Bipin'],
'Sales': [1000,300,400,500,800,1000,500,700,50,60,1000,900,750,200,300,1000,900,250,750,50],
'Quarter': [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4], 'State': ['Rajasthan','Panjab','Gujarat','Goa','Rajasthan','Gujarat','Panjab','Gujarat','Rajasthan','Rajasthan','Rajasth an','Panjab','Gujarat','Goa','Gujarat','Panjab','Panjab','Gujarat','Goa','Rajasthan'] } df = DataFrame(Employees, columns= ['Name of Employee', 'Sales','Quarter','State']) print (df) pivot = df.pivot_table(index=['State'], values=['Sales'], aggfunc={'median','mean','min'}) print (pivot)
OUTPUT
Sales
mean
median
min
State
Goa
483.333333
500.0
200.0
Gujarat
566.666667
550.0
250.0
Panjab
720.000000
900.0
300.0
Rajasthan
493.333333
430.0
50.0
#Python Program to create the dataframe with following
values
name 0 Mohak 1 Rajesh 2 Freya 3 Aditya 4 Anika
year
score
catches
2012
10
2
2012
22
2
2013
11
3
2014
32
3
2014
23
3
import pandas as pd data = {'name': ['Mohak', 'Rajesh', 'Freya', 'Aditya', 'Anika'],
'year': [2012, 2012, 2013, 2014, 2014], 'score': [10, 22, 11, 32, 23], 'catches': [2, 2, 3, 3, 3]} df = pd.DataFrame(data, columns= ['name', 'year','score','catches']) print(df)
#Sort the dataframe's rows by score, in descending order
import pandas as pd data = {'name': ['Mohak', 'Rajesh', 'Freya', 'Aditya', 'Anika'],
'year': [2012, 2012, 2013, 2014, 2014], 'score': [10, 22, 11, 32, 23], 'catches': [2, 2, 3, 3, 3]} df = pd.DataFrame(data, columns= ['name', 'year','score','catches']) print(df) r=df.sort_values(by='score', ascending=False) print(r)
OUTPUT name
3 Aditya 4 Anika 1 Rajesh 2 Freya 0 Mohak
year score catches 2014 32 3 2014 23 3 2012 22 2 2013 11 3 2012 10 2
#Sort the dataframe's rows by catches and then by score, in ascending order/sort by multiple columns
import pandas as pd data = {'name': ['Mohak', 'Rajesh', 'Freya', 'Aditya', 'Anika'],
'year': [2012, 2012, 2013, 2014, 2014], 'score': [10, 22, 11, 32, 23], 'catches': [2, 2, 3, 3, 3]} df = pd.DataFrame(data, columns= ['name', 'year','score','catches']) print(df) r=df.sort_values(by=['catches', 'score']) print(r)
OUTPUT
name 0 Mohak 1 Rajesh 2 Freya 4 Anika 3 Aditya
year score catches 2012 10 2 2012 22 2 2013 11 3 2014 23 3 2014 32 3
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